Innovative hull cleaning robot design and control by Laguerre base model predictive control for impedance and vibration management

Abstract

The intricate and unpredictable nature of underwater environments and disturbances necessitates the use of model predictive control for the effective operation and inspection of remotely operated vehicles (ROVs). This paper presented an innovative suspension system for a hull‐cleaning robot to control impedance while reducing the vibration of ROV brushes in the presence of environmental disturbances and uncertainties. The use of a model predictive controller that utilizes Laguerre functions results significant reduction in tracking time, and the efficiency of the proposed controller is demonstrated through successful impedance tracking in Z‐direction and vibration reduction in Z and Y directions of the robot in an uncertain environment with disturbance. A prototype robot is built and the controller performance is validated in a real condition and modal analysis theory output with experimental data. The results highlight the effectiveness of the designed suspension system and the developed MPC for real‐world applications where environmental conditions are unpredictable or subject to change while the robot is needed to clean the surface perfectly without scratching the hull.